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Last week the US National Cancer Institute announced a phase II clinical trial to test everolimus, a derivative of rapamycin, in BHD patients with renal cell carcinoma (RCC). The trial is also open to sporadic chromophobe RCC (chRCC) patients. Approximately 85% of BHD-RCC is either chRCC or a chromophobe-oncocytoma hybrid (Pavlovich et al., 2002), but there are no effective treatments available for this RCC subtype. Instead BHD patients undergo partial nephrectomies to excise tumours – while not often impacting greatly on renal function, repetitive surgeries can increase morbidity risks. It is hoped that cancer drugs, such as everolimus, can offer a valid alternative treatment.

Rapamycin, originally an immunosuppressant, is appealing as a cancer treatment due to its anti-proliferative properties – a result of mTOR signalling inhibition. Everolimus, and temsirolimus, were forms of rapamycin derived to have improved hydrophilicity (enabling oral and intravenous use), improved pharmacokinetics, and reduced immunosuppressive and toxic effects. They, like rapamycin, bind FKBP2 to inhibit mTORC1 signalling; a pathway found to be upregulated in a wide range of cancers (Moschetta et al., 2014).

The choice to trial everolimus in BHD patients is based on research that has found increased mTOR signalling in patient RCC and lung cyst samples, BHD cell lines and BHD-mouse kidney tumours (Baba et al., 2008, Hasumi et al., 2009, Nishii et al., 2013). In addition, preclinical studies in mouse models have found that treatment with rapamycin can reduce kidney cyst and tumour growth, and extend life span (Baba et al., 2008 , Chen et al., 2015). There have also been several case reports of BHD patients responding well to everolimus as part of their treatment programme (Nakamura et al., 2013, Benusiglio et al 2014) providing further support for the concept of the trial.

However, the relationship between FLCN and mTOR signalling is not fully understood, and may show tissue-specificity, as other groups have reported reduced mTOR signalling in human cell lines and mice renal cysts (Hartman et al., 2009, Bastola et al., 2013). As such everolimus may not be an effective treatment for all, or even any, BHD pathologies.

Everolimus is already approved as a second line treatment for metastatic RCC, some breast and pancreatic cancers, and subependymal giant cell astrocytoma (SEGA) in TSC patients. There are currently several hundred ongoing clinical trials assessing everolimus in a range of cancers and neurological disorders. In addition it is being trialled in LAM patients to assess impact on pulmonary pathologies (Goldberg et al., 2015) – sirolimus has already been found to halt the progression of lung cyst formation (McCormack et al., 2011) and is an approved treatment for angiomyolipomas in LAM and TSC patients. Topical sirolimus can also be used to treat facial angiofibromas in TSC patients (DeKlotz et al., 2011) but a recent trial assessing its use as a fibrofolliculoma treatment produced inconclusive results (Gijezen et al., 2014) – further discussion of this trial can be found here.

FLCN loss perturbs several signalling pathways, so the optimal treatment for BHD-RCC might be a combination of inhibitors. There are ongoing clinical trials accessing the safety and efficacy of combinatorial or sequential treatment of an mTOR inhibitor and a tyrosine kinase inhibitor (TKI), such as pazopanib or sunitinib, in a range of cancers including metastatic RCC. Further research will also increase our understanding of the biological changes responsible for tumour development in BHD and could help in the development of further targeted treatment options.

A recent blog post discussed the need to assess the pathogenicity of genetic variants to determine which mutations are truly causative and which are only background. This is highly important in the search for new cancer drugs as rapidly dividing tissues are more prone to accruing mutations. Large cancer genomic studies are identifying increasing numbers of apparently “significantly-mutated genes” across all major cancer types. However, these genes often include highly unlikely candidates. Analysis of 178 squamous lung cell carcinomas identified 450 significantly-mutated genes; almost a quarter of which were olfactory receptors (TCGA Research Network, 2012). It is necessary to be able to eliminate these false-positives and retain focus on true cancer-genes.

Significantly-mutated genes are identified as harbouring more mutations than expected given the average background mutation rate for the cancer type (Kan et al., 2010). Recent research from Lawrence et al., (2013) has determined significant background mutation frequency heterogeneity across cancer types and the genome as contributing to misidentification of “significantly-mutated” cancer-genes. To account for this heterogeneity they have developed MutSigCV – analytic software which incorporates more sample-specific mutation rates – to help identify which mutated genes are truly associated with cancer.

Lawrence et al. analysed 3,083 tumour-normal pairs across 27 tumour types, including clear cell and papillary Renal Cell Carcinoma (RCC), using whole-exome or whole-genome sequences. They identified 373,909 non-silent coding mutations over all, with an average of 4/Mb and median of 1.5/Mb per sample.

Comparison of individual patient mutation rates within and between cancer types identified variation over 1000-fold. Some variation is based on tumour origin tissue: melanoma and lung cancer samples, from tissues typically exposed to high levels of UV and smoke-based carcinogens respectively, exceeded 100 mutation/Mb compared to paediatric cancers, with less exposure to carcinogens, at around 0.1/Mb. However, there were also magnitudes of difference in variation between patients with the same cancer that could be due to inherited mutations, rather than acquired mutations, driving tumour development.

Lawrence et al. also found regional heterogeneity, up to 5-fold difference, in mutation rates across the genome. There was a strong correlation between high mutation and both low expression rate and late DNA replication. This correlation has been previously reported in germline cells potentially associated with low transcription-coupled repair levels (Fousteri & Mullenders, 2008) and a reduction in available nucleotides later in replication (Stamatoyannopoulous et al., 2009). An increased background mutation rate can explain a large number of the spurious squamous lung cell carcinoma cancer-genes identified as they are both low expression and late replicating genes.

Reanalysis of the original squamous lung cell carcinoma samples using MutSigCV software identified only 11 genes as significantly mutated (TCGA Research Network, 2012). These included genes previous reported to be associated with cancers and one novel gene – HLA-A – suggesting a role for immune evasion in tumourigenesis, an avenue that requires further follow up.

Lawrence et al. acknowledge that there are still other forms of heterogeneity that should be investigated including the co-occurrence of mutations in close proximity and heterogeneity across cancer cells within a tumour. The latter could be important in studies of diseases such as BHD where RCCs of multiple histologies develop and a high proportion of tumours are hybrids (Benusiglio et al., 2014). Although the main tumour driving force in BHD is the loss of FLCN, the development of different tumour types suggests additional mutations resulting in varied histologies. Identifying these mutations could help identify new treatment targets, but to do so it is necessary to separate true cancer-genes from background mutations.

As discussed in last week’s blog renal cell carcinoma (RCC) cells show altered metabolism favouring lactate fermentation as the major energy source. Such metabolic changes can be a response to hypoxia or mutations in genes, such as VHL, that disrupt HIFα-proteasomal degradation. HIF signalling, directly and indirectly, regulates over 2% of human genes including those involved in angiogenesis, survival, proliferation and metabolism (Manalo et al., 2005). Hypoxia and VHL-loss are generally thought to result in the same changes in gene and protein expression, however, Leisz et al., (2015) have found differential effects in RCC cellular models.

Differential effects of hypoxia and VHL-loss were assessed in three VHL-deficient cell lines – 786-O, RRC4 and RCC10 – alongside VHL transfectant counterparts, cultured in normoxic and hypoxic conditions. VHL expression in the transfectant lines was confirmed in both conditions, and HIFα-degradation in normoxia but not hypoxia indicated that the pVHL was functional. Leisz et al. used cDNA microarrays and 2-DE-based proteomics to identify changes in gene expression and protein levels in these cells.

Microarray results identified the greatest changes in gene expression between normoxic VHL+ cells and normoxic VHL- cells representative of the significant impact of VHL-loss. However, there were still differences in expression between hypoxic VHL- cells and normoxic VHL- cells suggesting that there are some VHL-independent hypoxia-dependent changes. In total 662 putative VHL-regulated genes and 194 putative hypoxia-regulated genes were identified. Proteomic analysis identified 76 differentially expressed proteins which could also be segregated into VHL-dependent and hypoxia-dependent targets.

In response to hypoxia cell metabolism switches to aerobic glycolysis with a high glucose influx and increased lactate production – the same changes are found in cancer cells (Warburg, 1956). The largest proportion of differentially expressed genes and proteins identified by Leisz et al. were metabolic – 24% of genes and 30% of proteins regulated by VHL-expression and 28% genes and 38% of proteins regulated by hypoxia.

Lee et al., (2015) recently described a HIF-independent lactate-induced hypoxia response mediated by NDRG3 that alters expression of numerous genes. This secondary hypoxia response would also be induced in VHL- cells due to reduced post-transcriptional VHL-mediated ubiquitination of NDRG3, thereby contribute to the changes in expression in both situations.

Inoperable RCC tends to be resistant to chemotherapy and radiotherapy. Whilst advances in targeted treatments have increased patient survival, tumours often develop resistance. Leisz et al. found that although a large number of genes are concordantly regulated by VHL-status and hypoxia, there are some VHL-dependent, VHL-independent, hypoxia-dependent and hypoxia independent genes and proteins that have differential effects on the metabolic switch in RCC. Identifying the different impact of hypoxia-responses based on true oxygen deprivation and those due to mutations in genes such as VHL and FLCN, which artificially increase HIF-2a signalling, could be important for the development of new treatments for RCC.

It is well established that altered metabolism in cancer cells supports survival and growth. Understanding these biological changes could lead to treatments able to specifically target tumourigenic cells. However, despite the known variability in tumour biology, the majority of research is based on the same available cell lines. In renal cell carcinoma (RCC) research these lines frequently carry a VHL mutation: VHL gene alterations are associated with hereditary RCC in VHL syndrome and up to 91% of sporadic clear cell RCCs (Nickerson et al., 2008). The loss of pVHL results in aberrant HIF signalling and changes in metabolism (Keefe et al., 2013).

New research from Wettersten et al. (2015) used metabolomics and proteomics to study metabolic changes in human RCC samples of defined grades (Fuhrman et al., 1982), validating findings in two RCC cell lines – 786-O (VHLm/-)* and Caki-1 (VHL+/+). They found that there are tumour grade-dependent metabolic changes with higher grade tumours showing increased levels of glutamine, fatty acid and glutathione metabolic reprogramming.

Normally pyruvate produced by glycolysis is converted to oxaloacetate and fed into the TCA cycle as the major source of cellular energy. Tumour cells show increased glycolysis but direct the resulting pyruvate towards lactate metabolism (Warburg, 1956). Wettersten et al., confirmed that in higher grade RCC tumours there were increased glycolysis metabolites but a decrease in pyruvate carboxylase and oxaloacetate levels. Instead increased lactate dehydrogenase (LDHA) and lactate concentrations indicated that lactose fermentation was the major energy source. Reduced viability of 786-O and Caki-1 cells in glucose deprivation culture conditions or in the presence of glycolysis inhibitor 2-DG demonstrated the high dependence of tumour cells on glucose and glycolysis respectively.

Under normal conditions fatty acid β-oxidation produces acetyl-CoA that can be utilised in the TCA cycle for energy production. Wettersten et al. reported a reduction in short fatty acids levels in higher grade tumours, indicative of increased metabolism, but a reduction in β-oxidation enzymes resulting in reduced oxidation of intermediate acyl-CoA and build-up of acylcarnitines. Previously high levels of carnitine and acylcarnitines have been report in RCC patient urine (Ganti et al., 2012).

Glutamine can feed into the TCA cycle, into the urea cycle, and into the glutathione (GSH) pathway (Smith, 1990). In the RCC tumour samples the TCA and urea cycle enzymes were downregulated. Instead the markedly higher levels of GSH indicated that more glutamine was being used to alleviate oxidative stress providing the cells with a survival advantage. This reliance on glutamine was demonstrated by reduced viability of 786-O and Caki-1 cells in glutamine deprivation culture conditions associated with reduced levels of GSH and its redox partner GSSG.

RCC in BHD patients also show increased lactate production and decreased fatty acid oxidation indicative of a metabolic shift (Preston et al., 2011). In BHD and other subtypes of RCC tumourigenesis is associated with mutations in other genes such as FLCN (BHD), TSC1 or TSC2 (TSC) and fumarate hydratase (HLRCC). Identifying distinct metabolic and signalling changes in these tumours could determine the impact of different mutations and identify specific treatment targets.

Wettersten et al. suggest that understanding more about the distinct metabolic changes in different cancer grades could lead to targeted grade-based treatments. Current RCC targeted treatments are based on kinase inhibition to repress aberrant signalling pathways. Further understanding of different tumour subtypes could enable future patients to receive highly effective mutation- and grade-based treatments.

* 786-O cells harbor an inactivating mutation in one VHL allele while the second allele is deleted.

Animal models can be useful for understanding disease pathology and as preclinical models for drug testing. As BHD patients develop renal cell carcinomas (RCCs) of varied histologies, associated with a loss of FLCN, BHD animal models could be used to study of a wide range of renal cancer subtypes. Current BHD mouse models include kidney-specific Flcn-knockouts (Chen et al., 2008, Baba et al., 2008) and ubiquitous knockouts (Hasumi et al., 2009, Hartman et al., 2009, Hudon et al., 2010). The former develop polycystic kidneys and die within three weeks, the latter can only be studied as heterozygotes with tumourigenesis dependent on a “second hit” resulting in variable penetrance and making them less suitable for drug studies.

Renal cysts developed in all homozygous knockout mice (n=100) – in over 50% within the first month – but were rarely seen in heterozygous knockout (n=5/33) or wildtype (n=1/38) mice. Immunohistochemistry confirmed that the cysts had developed from proximal tubule cells and were Flcn-deficient. Where complete Flcn knockout was not achieved, mainly in younger mice, there was no evidence of cyst formation (Chen et al., 2015).

The majority of homozygous knockout mice developed RCC (n=41/54). Lower grade chromophobe RCC, oncocytomas and hybrid RCCs (most often seen in BHD patients) were more frequently identified in younger mice with increased prevalence of higher grade papillary RCC and clear cell RCC in aging mice. Whether high grade tumours are the result of lower grade tumour transformation over time is an area that requires further investigation. Only two heterozygous knockout mice developed renal tumours (at 27 and 29 months), a lower tumourigenic frequency than the ubiquitous heterozygous Flcn knockout models (Hasumi et al., 2009).

Tumours from homozygous knockout mice were negative for Flcn and showed increased levels of AKT, mTOR, MMP and TGFβ signalling compared to healthy tissue. Activation of the mTOR pathway has previously been reported as a feature of BHD-mouse RCC development (Chen et al., 2008, Baba et al., 2008). However, a loss of Flcn has previously been linked to reduced TGFβ signalling in human UOK-257 cells (Hong et al., 2010) and mouse embryonic stem cells (Cash et al., 2011); this discrepancy could represent a species-specific role for TGFβ in mouse renal tumourigenesis or be the result of tissue-specific functions.

Chen et al., confirmed the applicability of their mice to drug testing by treating mice with rapamycin for ten months (started at two months old). Comparison of drug and sham treated mice showed a vast reduction in cyst and tumour development; the kidneys of treated mice did contain cysts but the authors suggest that these developed before treatment began. Based on this they claim “rapamycin effectively inhibited the development of new cysts and tumours”, but was unable to reverse pre-existing damage. However, as the number of cysts was only assessed at one time point it is possible that cysts continued to develop but treatment with rapamycin resulted in markedly slower growth and restricted transformation into tumours.

This new Flcnflox/flox/Sglt2-Cre knockout BHD-RCC model clearly represents the developmental stages of human renal tumour progression: cyst development (months 1-4), hyperplasia (month 5), microtumours (from 6 months) and large tumours (from 12 months).The high and constant penetrance afforded by highly-tissue specific homozygous knockout coupled with early onset and longer lifespan compared to other kidney specific Flcn-knockout mice make them a powerful tool for understanding tumourigenesis and for preclinical testing.

Genetic sequencing is increasing diagnosis of pre-existing conditions, identifying which diseases a patient is at risk of developing, and which treatments they will best respond to. As the cost of genetic sequencing falls its use in clinical, research and private testing will continue to increase. Whilst we know that variation is a natural feature of the human genome, we are currently unable to accurately predict the effect on health, and the penetrance of this effect, for the majority of reported variants.

The variable pathogenicity of putative Loss-of-Function (pLOF) mutations was the focus of a recent paper by Johnston et al., (2015): genetic sequencing identified 103 individuals (from 951) carrying a pLOF mutation in a gene previously associated with haploinsufficiency pathologies. Of the 79 patients available for in depth clinical follow-up screening 43% had an individual or family history attributable to the variation. This included two undiagnosed BHD patients who can now be monitored for the development of renal cancer. However, 54% of these patients were positive for a pLOF variant but had no clinical indicators. This included a family carrying a mutation in the X-linked DMD gene, the cause of Duchenne muscular dystrophy, but with no evidence of muscle weakness in either male carrier. It is unknown whether these pLOF mutations are non-pathogenic variants or have variable penetrance. Potentially such patients could help identification modifier genes and increase understanding of disease pathology.

Determining whether a variant is non-pathogenic or non-penetrative is important both when a mutation is being sought and for incidental findings resulting from a more general genetic analysis. Patients should be warned in advance that mutations in disease-risk genes could be identified as a result of testing. The ACMG provides recommendations on reporting incidental findings (Green et al., 2013) but the variable penetrance of even well-known cancer-risk genes such as BRCA1 (Petrucelli et al., 2013) can make calculating risk complicated.

This difficulty in assessing the risk factors associated with genetic variants was highlighted in a recent review by ClinGen which reported variation in the interpretation of 17% of variants identified in more than one genetic lab (Rehm et al., 2015). These interpretations, stating either that a variation is non-pathogenic or highly pathogenic, could influence and potentially compromise patient care. Therefore it is essential that more accurate assessments of risk can be conducted.

The NCBI hosts a genetic variation database, ClinVar, which encourages private, clinical and research labs to submit genetic testing data which is then accessible to the wider research community (coded for anonymity). Currently over 300 different labs worldwide contribute data and over 172,000 variants in 23,000 genes have been reported. ClinGen are using this database to assess the clinical relevance of genomic variants – a large project as 71% of known variants are of “uncertain clinical significance” and even the majority of the 29% “likely or known to be pathogenic” have only been reported once (Rehm et al., 2015). The submission of further genetic data, both to general and disease-specific databases such as the LOVD-hosted FLCN mutation database, will enable researchers to make more robust assessments of individual variant pathogenicity.

Large scale sequencing projects such as the WGS500 and 100,000 Genomes Project can discover more about rare disease and cancer patients’ genomes, and potentially increase understanding of pathology (Taylor et al., 2015). However, to be able to accurately assess the risk factor of disease variants similar large sequencing projects in reportedly healthy individuals are required to identify variants that are common in the population and therefore most likely non-pathogenic. For now, even if variant risk cannot be accurately calculated, genetic sequencing enables identification of suspected pathogenic variants, which provides the basis for further clinical evaluation and care of patients and their families.

Rare diseases have become a more interesting target to the pharmaceutical industry as a result of incentives offered by the USA Orphan Drug Act (1983) and EU/141/2000 legislation, the increasing development costs and failure rate of common disease drugs, and the potential for rare disease drugs to influence common disease treatment. It is predicted that revenue from rare disease drugs will continue to rise and that more pharmaceutical companies will divert resources towards their development (Orphan Drug Report 2014). However, the traditional drug development methods are not optimal for rare diseases as experts and patients tend to be sparse. Arguably the best way around this issue is to collaborate with a patient group – the concept of last week’s Findacure workshop in London.

Patient groups are experts in the disease, know the expert clinicians, the researchers and, more importantly, the patients. They can help design more accessible and suitable clinical trials (see our previous blog on clinical trials for rare disease patients), and can facilitate more long-term patient follow-up. Collaborations are also beneficial to the patient groups as there is a focus on their disease, increasing awareness and knowledge, and their members gain access new clinical trials.

However, such collaborations are often scrutinised by external groups and accusations of undue influence can be damaging to the patient group who must maintain the trust of their patients and partners. As collaborations have such scope for treatment development, it is important that they be protected from such attacks and that all parties are comfortable with continued interactions. For this reason it is essential that collaborations have predefined rules of engagement, maintain transparency for all interactions, especially those with a financial incentive, and welcome external scrutiny and assessment. In addition the majority of pharmaceutical companies will have strict codes of conduct, often including regulations regarding patient group contact. It is important however that both parties should be involved in drafting a collaborative agreement ensuring that both group agendas are fairly represented.

Patient groups should play an active role in these collaborations; acting as a voice for their patients, chasing unanswered questions and ensuring data dissemination. However, for patient groups to ask the right kinds of questions and have a meaningful input, industrial partners must ensure they provide understandable information about ongoing work and results. A recent survey found that only 22% of the general public in several European countries were knowledgeable about drug discovery and clinical trials (EUPATI Public views on Medicine Development). To increase understanding among the public, and importantly within patient groups, organisations such as EUPATI provide training, workshops, webinars and online resource libraries to help in the development of the skills required to form mutually beneficially collaborations.

The power of patient groups to impact the development of rare disease treatments is likely to increase following the recent launch of Rare Disease International (RDI) – a global organisation advocating for recognition of rare diseases as an international public health and research priority, thereby increasing the services and support available to patients and their families. RDI aim to facilitate networking, increase education of rare diseases on a national and international level, and increase rare diseases representation in the pharmaceutical industry. They will also be able to offer support and guidance to individual patient groups considering collaborations.

However, one of the largest issues associated with the development of treatments for rare diseases cannot be influenced by these groups alone: the cost of treatments. Pharmaceutical companies must recuperate the costs associated with the R&D and clinical trials for any new treatments. Unfortunately the limited number of target patients for any single rare disease most often results in these costs being extremely high per patient, severely limiting access. It is only through an overhaul of the pricing structures, and questioning profit after recuperation, that this issue can be addresses and newly developed treatments can be accessed by those most in need.